TM 720 - Lecture 01

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TM 720 - Lecture 01

• Introduction to Statistical Process Control

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Agenda

• Introductions
• Course Overview
• Materials
• Expectations
• Questions Issues
• Data Collection
• Red Bead Experiment

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TM 720

• Lecturer
• D. H. Jensen
• 322 Civil Mechanical Bldg
• [phone]
• Dean.Jensen_at_sdsmt.edu
• Office Hours
• M, W, F 1100 - 1150 AM (Mountain Time)
• Class Meetings
• Wednesdays
• 600 PM 900 PM, CB 110

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Background

• Academic
• Industrial Engineering, Engineering Management,
  Technology Management
• South Dakota School of Mines Technology
• Industrial Manufacturing Engineering
• Oregon State University
• Ph.D. Industrial Engineering
• University of Iowa
• M.A. Technology - Supervision Management
• University of Northern Iowa
• B.S. Computer Engineering
• Iowa State University

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Background

• Industry Experience
• Land Surveying Crew
• Data Systems Manager
• Programmer
• Network Engineering
• Plant Engineering
• Manufacturing Engineering
• Design Engineering
• Hazardous Waste Management

• Plant Administration
• 7 plants, 3 towns
• Consulting
• Commercial Avionics
• Medical Supplies
• Air Force Naval Fleet Maintenance Facilities
• Die Cast Foundry
• Farm Toys
• Semiconductor Fab

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Course Overview

• Students will demonstrate
• the ability to prepare and interprete Pareto,
  Cause Effect, Scatter, Checksheet, Defect
  Concentration, and Histogram charts and diagrams.
  
• a knowledge of the fundamentals of statistical
  process control chance and assignable causes,
  the meaning of statistical control, average run
  length (ARL), operating characteristic (OC)
  curve, the principles of rational subgroup
  formation, and runs tests.

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Learning Objectives

• Students will demonstrate
• the ability to construct and interpret control
  charts for variables and attributes from
  standards or data.
• the ability to construct and interpret control
  charts for individual measurements and short-run
  SPC from standards or data.
• the ability to calculate and interpret process
  capability ratios (Cp, Cpk, Cpm) and gage
  repeatability and reproducibility.

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Learning Objectives

• Students will demonstrate
• an introductory knowledge of acceptance sampling
  principles and the ability to design, implement,
  and use acceptance sampling plans and military
  standards.
• an introductory knowledge of the principles,
  calculations, and interpretation of designed
  experiments

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Differences Between Undergraduate Graduate SQC

• Students expect
• To be graded primarily on their ability to
  provide correct answers to a presented situation.
• Grade based on HW and Exams
• To be able to identify, apply, and interpret the
  most appropriate model for an uncovered situation
  (an opportunity) including justification and
  possible modification of a model.
• Grade based on Exams (and class contribution)

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Course Overview

• See Schedule Page for details
• Basic problem solving tools and process
  comparisons covered on Exam I.
• Control charting for continuous, discrete,
  individuals, and short run SPC on Exam II.
• Acceptance sampling and an intro to designed
  experiments on Final Exam.

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Required Materials

• Textbook
• Montgomery, D. C. (2009). Introduction to
  Statistical Quality Control (6th ed).
• New York NY John Wiley Sons.
• ISBN 978-0-470-16992-6 (required)
• Engineering Notebook
• 9-3/4" x 7-1/2", 5x5 quad-ruled, 80-100 pp.
  (approx.).

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Recommended Materials

• Engineering/Scientific calculator
• Engineering Problems Paper
• 8-1/2" x 11", three hole drilled, ruled five
  squares/division, 50 pp. (approx.).
• Mechanical Pencil
• 0.5 mm, HB or B lead with comfortable grip
• Plastic-based Eraser
• clickable pen-style suggested

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Expectations

• Grading Scale
• A 90 B 80 C 70 D 60
• F lt 60
• Weighting
• Midterm Exam I 30
• Midterm Exam II 35
• Final Exam 35

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Expectations

• Assignments
• Assignments will NOT be turned in
• Solutions will be posted on-line (sometime later)
• Exams
• Exams are open Engineering notebook and closed
  textbook and homework.
• Most necessary tables and diagrams are online
  (Matls pg) these should be placed in your
  Engineering Notebook.

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Expectations

• Make-up Work (Exams)
• Make-Up work is the students responsibility, and
  is arranged at the lecturers discretion.
  Policies
• Foreseeable Circumstances - contact the lecturer
  as far in advance as possible (e-mail).
• Unforeseeable Circumstances - contact the
  lecturer as soon as practical (leave phone
  message).
• Note that it is NOT possible to arrange a make-up
  FINAL for anything other than University approved
  circumstances (medical, disability, multiple
  exams).

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Expectations

• Academic Honesty
• OK to work together on HW for this class
• as long as what appears on your sheet is your
  work, your words, and your writing
• OK to copy my materials for this class
• download and print slides to your engineering
  notebook for this class
• download and use my spreadsheet templates for
  your assignments and practice in this course
• Exams are always individual work

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Questions Issues

• Students with special needs or requiring special
  accommodations should contact the instructor, Dr.
  Jensen, at 394-1278 and/or the campus ADA
  coordinator, Jolie McCoy, at 394-1924 at the
  earliest opportunity.

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Data Collection
Name Course ID Preferred name Term /
Year E-mail address On-Campus/Distance Your
major Hometown Contact Info for Proctor
(Distance, only) Anything else the instructor
should know about you
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Demings Red Bead Experiment

• Personnel Needed
• Accountant
• Inspectors
• Operators
• Board of Directors
• Consultant
• Plant Manager (Dr. Jensen)